Background

The Youth Barometer, or UB for short, tackles the challenge of understanding the complex characteristics of millennials. Decades ago, young adults fell into only a couple of lifestyle categories. Now, people in the millennial generation fall into far more categories and lifestyles, making it challenging for brands to communicate with them.

Even though UB’s focus is on millennials, their research isn’t limited to that deeply studied age group. UB gathers survey data and generates insights for young as well as older people. Like most research organizations, UB helps companies understand the types of products or services their target audience is interested in. Together with the research, UB assists their clients to make more informed decisions about entering new markets or developing new products and services.

Challenge

UB faced multiple challenges when working with very large, quantitative datasets. The surveys they were administering would often generate over 20,000 respondents, which meant UB had three main requirements when searching for a survey data analysis solution. Specifically, it had to be:

Powerful enough to process and analyze datasets with thousands of respondents

Specifically tailored for survey data and market research data formats

Simple and intuitive to allow for easy editing of variables and response data

When considering Tableau, they found that Tableau’s analytical capabilities and crosstabbing tools were not meant to handle 20,000-respondent datasets. Additionally, it wasn’t easy to edit or weight variables in the tool.

Working with variables and interpreting findings in SPSS was not an intuitive process for UB, as the platform lacked the ease-of-use needed to conduct analysis and interpret findings quickly. The complexity of SPSS coupled with the size of the datasets UB was working with made it far from ideal for analyzing UB’s data.

UB realized that using SPSS and Tableau would not have been an efficient choice for their team, because those tools would not be resource and time-effective for multiple analysts to collaborate on one dataset.

Solution

UB selected MarketSight as their solution of choice for analyzing large datasets with a high degree of respondent complexity, to provide their clients with data-driven insights.

MarketSight’s cloud-based platform is designed specifically for analyzing and visualizing survey data, and works with datasets from all major survey data platforms. Additionally, integrations with survey tools like Confirmit, Qualtrics, Google Surveys, CMIX, and others, allow the platform to always reflect the latest insights in Charts and Dashboards created in MarketSight. Uploading data from most major survey tools into MarketSight is a trouble-free task, as there’s no need to code respondents, and variable preferences such as weighting are carried over from the survey tool.

Magnus Kjellman, Quantitative Analyst at UB, says “We use Confirmit for our survey data collection, which has a direct integration with MarketSight. As our tracker studies gather new data in Confirmit, that data is automatically reflected in MarketSight. The data could be very messy in our survey tool as a result of respondents partially completing surveys or giving very unique responses. Regardless of this, MarketSight accepts and comprehends all of the data for us to interpret.”

The ability to do both simple and advanced analysis in MarketSight gives UB the flexibility to interpret their survey data findings with ease. The functions which help UB’s analysis efforts the most are MarketSight’s ability to:

“MarketSight is more than a data viewing tool. In seconds, we can use the platform to easily weight or append variables, customize the contents of a dataset for a client’s needs, or change the elements of a crosstab,” Magnus adds.

“The feature-rich platform provides a lot of value to us. Using MarketSight as our data analysis solution grants us large amounts of freedom when working with our survey data. We don’t have to go back and forth between tools; we can do everything in MarketSight. We can be much more iterative in the ways we work.”

Results

UB has experienced a significant improvement in their speed and ability to generate insights since adopting MarketSight. The benefits to the business and the team’s workflow include:

Going from 2 days to 2 hours lead time between closing a survey and starting their analysis

Ability to make more focused client reports

Hours saved by using automated functions which were manual and required more expertise when using SPSS

Seamless upload and analysis of large datasets using MarketSight’s High Capacity servers

Magnus summarizes UB’s experience with MarketSight in this way: “The data that UB receives and analyzes is important, but it’s even more important to deliver real insights, which MarketSight empowers us to do with less time and work than before.”